PrymeIntelligence

Training teams for AI agents·Answer

How do you train staff to read an AI agent’s decision record?

Train staff to read an AI agent's decision record by teaching the verdict, the deciding bound and the provenance of each source, then practising on real entries.

Teach three readings in order: the verdict, the bound that decided it, and the sources behind it. Then practise on real entries from your own operation until staff can explain any decision in a sentence. Reading a decision record is a skill like reading a ledger, and it is learned by doing, not by watching a demonstration.

What is in an agent's decision record?

Every action an agent attempts is filed in an append-only record. Each entry shows what the agent tried to do, the verdict it received, which of the five bounds decided that verdict, and the facts the agent relied on, each stamped with where it came from.

Staff who can read an entry can answer the questions that matter after the fact: why was this refund held, why did the agent refuse that payment, and was the agent right to trust the document it used? Staff who cannot read it will escalate every question to someone technical, and the record stops being useful to the people closest to the work.

What are the three readings?

1. The verdict

There are four. Allowed means the agent acted within all its bounds. Held means it drafted the action and is waiting for a named person. Refused means the action was outside the agent's bounds. Withheld means the action exists but the platform blocks it for every agent at every depth.

The first lesson is that refused and withheld are different. A refused action may become allowed if the business changes its limits or the agent earns more depth. A withheld action will not, whatever anyone configures.

2. The deciding bound

Every action meets five bounds at once: role scope, certificate, sources, the business's own limits and the platform guardrails. The lowest one wins, and the entry names it. Staff should learn to read "held: customer limit" or "refused: certificate" and know where to look next.

3. The sources and their provenance

Each fact arrives stamped as sealed, signed, declared or external, strongest first. A balance from the core ledger is sealed. A customer's statement of income is declared. An emailed invoice is external, and an external claim cannot authorise a payment. Staff should check whether the agent leaned on a weak source for a strong decision.

How do you build the skill?

  1. Start with five entries. Choose one of each verdict plus one entry where the deciding bound was a lapsed certificate. Walk through them together.
  2. Hand out ten more. Each person writes one sentence per entry: what happened, what decided it, and which source carried the weight.
  3. Compare sentences. Where people disagree, the disagreement is the lesson.
  4. Reconstruct one disputed case. Take a real complaint and rebuild the decision from the record alone, as set out in how to reconstruct an AI agent's decision from the record.
  5. Repeat monthly with fresh entries, including any new verdict types the team has not seen.

What does a worked example look like?

Take an accounts team at a mid-sized distributor. The record shows a supplier payment of 4,000, verdict held, deciding bound "sources". The agent had a matched purchase order and goods receipt, both sealed, but the bank details came from an email, which is external.

A trained clerk reads that entry in seconds: the agent did its job, the payment is waiting for a person because the account change has not been confirmed through a signed channel, and nothing should be released until it is. An untrained clerk sees "held" and approves to clear the queue.

What should staff record about their own reading?

Their decisions join the same record. An approval or decline with a written reason is evidence that a person read the entry, not just clicked. That evidence is distinct from the learner's own training record, which shows they were taught. Both matter to an auditor, and regulated firms may also map this practice to record-keeping duties, as discussed in training staff to read and use agent logs under Article 12.

For where this sits in a wider programme, see training teams for AI agents.

Where the Academy fits

Reading the record runs through the Operator track of Pryme Intelligence Academy, in modules on how a governed agent decides, reading the workspace and what to do when something goes wrong. Learners practise on the real product in a free Build workspace, and module tests are set in their own industry and role, so the entries they read look like their own work.

Questions people ask

Who needs to read the record besides reviewers?

Team leads, complaints handlers, compliance and internal audit. Each reads it for a different reason, but all need the same three readings.

How long does it take before staff read entries confidently?

Most of the learning happens in the first few dozen real entries with feedback. Plan for regular practice over several weeks rather than a single session.

Can staff edit the record if they spot a mistake?

No. The record is append-only. A correction is a new entry that refers to the old one, which is what lets anyone reconstruct the decision later.

Train the people who run your agents.

Pryme Intelligence Academy: free courses on the real product, audio lessons, labs in a free workspace, and certificates anyone can check on VerifyDoc.ai. Teams get seats, an admin view and a free readiness assessment.